viz1

#devtools::install_github("slowkow/ggrepel")
library(ggrepel)

## Loading required package: ggplot2

## Warning: package 'ggplot2' was built under R version 4.1.2

library(tidyverse)

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## ✔ purrr   0.3.4

## Warning: package 'tibble' was built under R version 4.1.2

## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
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library(readr)
library(dplyr)
library(ggplot2)
library(plotly)

## 
## Attaching package: 'plotly'

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vizdata <- read_csv("viz1data.csv")

## Rows: 111 Columns: 5── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): field
## dbl (4): mean_borrow, mean_income, sample_borrow, sample_income
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

vizdata1 <- vizdata %>%
  filter(field !="Total")

set.seed(123)
ggplot(vizdata1, aes(x=mean_borrow,y=mean_income,label=field)) +
  geom_point(size = 2.5, color = "#00AFBB") +
  geom_text_repel(aes(label=field), size=2.25, box.padding = 0.5, segment.size = 0.25) +
  xlim(3500,15000) + ylim(60000,110000) +
  theme_classic() +
  xlab("Mean Cumulative Amount Borrowed For Undergrad in 2016") +
  ylab("Mean Parents' Income") +
  theme(panel.border = element_rect(color = "black", fill = NA, size = 1))

fig <- plot_ly(vizdata1, x = ~mean_borrow, y = ~mean_income, text = vizdata1$field, type = 'scatter', mode = 'markers', name = 'Tips')
fig